IDEAS home Printed from https://ideas.repec.org/f/pfo214.html
   My authors  Follow this author

Catherine Scipione Forbes

Personal Details

First Name:Catherine
Middle Name:Scipione
Last Name:Forbes
Suffix:
RePEc Short-ID:pfo214
[This author has chosen not to make the email address public]
http://www.buseco.monash.edu.au/ebs/people/profile.php?sn=scipione
Department of Econometrics and Business Statistics PO Box 11E, level 6 Monash University, Victoria 3800 Australia
+61 3 9905 2471

Affiliation

Department of Econometrics and Business Statistics
Monash Business School
Monash University

Melbourne, Australia
http://business.monash.edu/econometrics-and-business-statistics

: 03 990 52372
03 990 55474
Room 674, Menzies Building, Wellington Road, Clayton, Victoria, 3168
RePEc:edi:dxmonau (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Worapree Maneesoonthorn & Catherine S. Forbes & Gael M. Martin, 2014. "Inference on Self-Exciting Jumps in Prices and Volatility using High Frequency Measures," Papers 1401.3911, arXiv.org, revised Mar 2016.
  2. Jason Ng & Catherine S. Forbes & Gael M. Martin & Brendan P.M. McCabe, 2011. "Non-Parametric Estimation of Forecast Distributions in Non-Gaussian, Non-linear State Space Models," Monash Econometrics and Business Statistics Working Papers 11/11, Monash University, Department of Econometrics and Business Statistics.
  3. Susan Tregeagle & Elizabeth Cox & Catherine Forbes & Cathy Humphreys & Cas O'Neill, 2011. "Worker time and the cost of stability," Monash Econometrics and Business Statistics Working Papers 2/11, Monash University, Department of Econometrics and Business Statistics.
  4. Worapree Maneesoonthorn & Gael M. Martin & Catherine S. Forbes & Simone Grose, 2010. "Probabilistic Forecasts of Volatility and its Risk Premia," Monash Econometrics and Business Statistics Working Papers 22/10, Monash University, Department of Econometrics and Business Statistics.
  5. Chris M Strickland & Gael Martin & Catherine S Forbes, 2006. "Parameterisation and Efficient MCMC Estimation of Non-Gaussian State Space Models," Monash Econometrics and Business Statistics Working Papers 22/06, Monash University, Department of Econometrics and Business Statistics.
  6. Catherine Forbes & Brett Inder & Sunitha Raman, 2006. "Measuring the cost of leaving care in Victoria," Monash Econometrics and Business Statistics Working Papers 18/06, Monash University, Department of Econometrics and Business Statistics.
  7. Gael Martin & Chris Strickland & Catherine Forbes, 2004. "Bayesian Estimation of Non-Gausian Time Series with Applicaitons to Transaction Data," Econometric Society 2004 Australasian Meetings 324, Econometric Society.
  8. Chris M. Strickland & Catherine S. Forbes & Gael M. Martin, 2003. "Bayesian Analysis of the Stochastic Conditional Duration Model," Monash Econometrics and Business Statistics Working Papers 14/03, Monash University, Department of Econometrics and Business Statistics.
  9. Rachel Campbell & Catherine S. Forbes & Kees Koedijk & Paul Kofman, 2003. "Diversification Meltdown or the Impact of Fat tails on Conditional Correlation?," Monash Econometrics and Business Statistics Working Papers 18/03, Monash University, Department of Econometrics and Business Statistics.
  10. Gael M. Martin & Catherine S. Forbes & Vance L. Martin, 2003. "Implicit Bayesian Inference Using Option Prices," Monash Econometrics and Business Statistics Working Papers 5/03, Monash University, Department of Econometrics and Business Statistics.
  11. Catherine S. Forbes & Gael M. Martin & Jill Wright, 2003. "Bayesian Estimation of a Stochastic Volatility Model Using Option and Spot Prices: Application of a Bivariate Kalman Filter," Monash Econometrics and Business Statistics Working Papers 17/03, Monash University, Department of Econometrics and Business Statistics.
  12. Ralph D. Snyder & Catherine S. Forbes, 2002. "Reconstructing the Kalman Filter for Stationary and Non Stationary Time Series," Monash Econometrics and Business Statistics Working Papers 14/02, Monash University, Department of Econometrics and Business Statistics.
  13. Brian Hanlon & Catherine Forbes, 2002. "Model Selection Criteria for Segmented Time Series from a Bayesian Approach to Information Compression," Monash Econometrics and Business Statistics Working Papers 8/02, Monash University, Department of Econometrics and Business Statistics.
  14. C.S. Forbes & G.M. Martin & J. Wright, 2002. "Bayesian Estimation of a Stochastic Volatility Model Using Option and Spot Prices," Monash Econometrics and Business Statistics Working Papers 2/02, Monash University, Department of Econometrics and Business Statistics.
  15. Roland G. Shami & Catherine S. Forbes, 2002. "Non-linear Modelling of the Australian Business Cycle using a Leading Indicator," Monash Econometrics and Business Statistics Working Papers 5/02, Monash University, Department of Econometrics and Business Statistics.
  16. Shami, R.G. & Forbes, C.S., 2000. "A structural Time Series Model with Markov Switching," Monash Econometrics and Business Statistics Working Papers 10/00, Monash University, Department of Econometrics and Business Statistics.
  17. Forbes, C.S. & Kofman, P., 2000. "Bayesian Soft Target Zones," Monash Econometrics and Business Statistics Working Papers 4/00, Monash University, Department of Econometrics and Business Statistics.
  18. Catherine S. Forbes & Paul Kofman, 2000. "Bayesian Target Zones," Econometric Society World Congress 2000 Contributed Papers 0575, Econometric Society.
  19. Forbes, C.S. & Snyder, R.D. & Shami, R.S., 2000. "Bayesian Exponential Smoothing," Monash Econometrics and Business Statistics Working Papers 7/00, Monash University, Department of Econometrics and Business Statistics.
  20. Snyder, R.D. & Forbes, C.S., 1999. "Understanding the Kalman Filter: an Object Oriented Programming Perspective," Monash Econometrics and Business Statistics Working Papers 14/99, Monash University, Department of Econometrics and Business Statistics.
  21. Oliver, J.J. & Forbes, C.S., 1997. "Bayesian Approaches to Segmenting A Simple Time Series," Monash Econometrics and Business Statistics Working Papers 14/97, Monash University, Department of Econometrics and Business Statistics.
  22. Forbes, C.S. & Kalb, G.R.J. & Kofman, P., 1997. "Bayesian Arbitrage Threshold Analysis," Monash Econometrics and Business Statistics Working Papers 3/97, Monash University, Department of Econometrics and Business Statistics.
  23. King, M.L. & Forbes, C.S. & Morgan, A., 1996. "Improved Small Sample Midel selection Procedures," Monash Econometrics and Business Statistics Working Papers 18/96, Monash University, Department of Econometrics and Business Statistics.
  24. Forbes, C.S. & King, M.L. & Morgan, A., 1995. "A Small Sample Variable Selection Procedure," Monash Econometrics and Business Statistics Working Papers 15/95, Monash University, Department of Econometrics and Business Statistics.
  25. Scipione, C.M., 1994. "Bayesian Statistical Variable Selection: A Review," Monash Econometrics and Business Statistics Working Papers 1/94, Monash University, Department of Econometrics and Business Statistics.

Articles

  1. Ng, Jason & Forbes, Catherine S. & Martin, Gael M. & McCabe, Brendan P.M., 2013. "Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models," International Journal of Forecasting, Elsevier, vol. 29(3), pages 411-430.
  2. Maneesoonthorn, Worapree & Martin, Gael M. & Forbes, Catherine S. & Grose, Simone D., 2012. "Probabilistic forecasts of volatility and its risk premia," Journal of Econometrics, Elsevier, vol. 171(2), pages 217-236.
  3. Tregeagle, Susan & Cox, Elizabeth & Forbes, Catherine & Humphreys, Cathy & O'Neill, Cas, 2011. "Worker time and the cost of stability," Children and Youth Services Review, Elsevier, vol. 33(7), pages 1149-1158, July.
  4. Strickland, Chris M. & Martin, Gael M. & Forbes, Catherine S., 2008. "Parameterisation and efficient MCMC estimation of non-Gaussian state space models," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2911-2930, February.
  5. Campbell, Rachel A.J. & Forbes, Catherine S. & Koedijk, Kees G. & Kofman, Paul, 2008. "Increasing correlations or just fat tails?," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 287-309, March.
  6. Catherine Forbes & Gael Martin & Jill Wright, 2007. "Inference for a Class of Stochastic Volatility Models Using Option and Spot Prices: Application of a Bivariate Kalman Filter," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 387-418.
  7. Strickland, Chris M. & Forbes, Catherine S. & Martin, Gael M., 2006. "Bayesian analysis of the stochastic conditional duration model," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2247-2267, May.
  8. Gael M. Martin & Catherine S. Forbes & Vance L. Martin, 2005. "Implicit Bayesian Inference Using Option Prices," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(3), pages 437-462, May.
  9. Snyder Ralph D & Forbes Catherine S, 2003. "Reconstructing the Kalman Filter for Stationary and Non Stationary Time Series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(2), pages 1-20, July.
  10. Forbes, Catherine S & Kalb, Guyonne R J & Kofman, Paul, 1999. "Bayesian Arbitrage Threshold Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 364-372, July.
  11. G. M. Martin & C. S. Forbes, 1999. "Using simulation methods for bayesian econometric models: inference, development and communication: some comments," Econometric Reviews, Taylor & Francis Journals, vol. 18(1), pages 113-118.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Worapree Maneesoonthorn & Catherine S. Forbes & Gael M. Martin, 2014. "Inference on Self-Exciting Jumps in Prices and Volatility using High Frequency Measures," Papers 1401.3911, arXiv.org, revised Mar 2016.

    Cited by:

    1. Bibinger, Markus & Neely, Christopher J. & Winkelmann, Lars, 2017. "Estimation of the discontinuous leverage effect: Evidence from the NASDAQ order book," Working Papers 2017-12, Federal Reserve Bank of St. Louis.
    2. David T. Frazier & Worapree Maneesoonthorn & Gael M. Martin & Brendan P.M. McCabe, 2018. "Approximate Bayesian forecasting," Monash Econometrics and Business Statistics Working Papers 2/18, Monash University, Department of Econometrics and Business Statistics.

  2. Jason Ng & Catherine S. Forbes & Gael M. Martin & Brendan P.M. McCabe, 2011. "Non-Parametric Estimation of Forecast Distributions in Non-Gaussian, Non-linear State Space Models," Monash Econometrics and Business Statistics Working Papers 11/11, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Gael M. Martin & Brendan P.M. McCabe & Worapree Maneesoonthorn & Christian P. Robert, 2014. "Approximate Bayesian Computation in State Space Models," Monash Econometrics and Business Statistics Working Papers 20/14, Monash University, Department of Econometrics and Business Statistics.
    2. Gael M. Martin & Brendan P.M. McCabe & David T. Frazier & Worapree Maneesoonthorn & Christian P. Robert, 2016. "Auxiliary Likelihood-Based Approximate Bayesian Computation in State Space Models," Monash Econometrics and Business Statistics Working Papers 09/16, Monash University, Department of Econometrics and Business Statistics.
    3. Pauwels, Laurent L. & Vasnev, Andrey L., 2016. "A note on the estimation of optimal weights for density forecast combinations," International Journal of Forecasting, Elsevier, vol. 32(2), pages 391-397.
    4. Patrick Leung & Catherine S. Forbes & Gael M. Martin & Brendan McCabe, 2016. "Data-driven particle Filters for particle Markov Chain Monte Carlo," Monash Econometrics and Business Statistics Working Papers 17/16, Monash University, Department of Econometrics and Business Statistics.

  3. Worapree Maneesoonthorn & Gael M. Martin & Catherine S. Forbes & Simone Grose, 2010. "Probabilistic Forecasts of Volatility and its Risk Premia," Monash Econometrics and Business Statistics Working Papers 22/10, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Worapree Maneesoonthorn & Gael M. Martin & Catherine S. Forbes, 2017. "Dynamic Price Jumps: the Performance of High Frequency Tests and Measures, and the Robustness of Inference," Papers 1708.09520, arXiv.org, revised Sep 2018.
    2. David Harris & Gael M. Martin & Indeewara Perera & Don S. Poskitt, 2017. "Construction and visualization of optimal confidence sets for frequentist distributional forecasts," Monash Econometrics and Business Statistics Working Papers 9/17, Monash University, Department of Econometrics and Business Statistics.
    3. Ng, Jason & Forbes, Catherine S. & Martin, Gael M. & McCabe, Brendan P.M., 2013. "Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models," International Journal of Forecasting, Elsevier, vol. 29(3), pages 411-430.
    4. Worapree Maneesoonthorn & Catherine S. Forbes & Gael M. Martin, 2013. "Inference on Self-Exciting Jumps in Prices and Volatility using High Frequency Measures," Monash Econometrics and Business Statistics Working Papers 28/13, Monash University, Department of Econometrics and Business Statistics.
    5. Perera, Indeewara & Koul, Hira L., 2017. "Fitting a two phase threshold multiplicative error model," Journal of Econometrics, Elsevier, vol. 197(2), pages 348-367.
    6. Hattori, Masazumi & Shim, Ilhyock & Sugihara, Yoshihiko, 2016. "Volatility Contagion across the Equity Markets of Developed and Emerging Market Economies," ADBI Working Papers 590, Asian Development Bank Institute.
    7. Hattori, Masazumi & Shim, Ilhyock & Sugihara, Yoshihiko, 2018. "Cross-stock market spillovers through variance risk premiums and equity flows," CIS Discussion paper series 667, Center for Intergenerational Studies, Institute of Economic Research, Hitotsubashi University.
    8. Worapree Maneesoonthorn & Gael M. Martin & Catherine S. Forbes, 2017. "Dynamic asset price jumps and the performance of high frequency tests and measures," Monash Econometrics and Business Statistics Working Papers 14/17, Monash University, Department of Econometrics and Business Statistics.
    9. David T. Frazier & Worapree Maneesoonthorn & Gael M. Martin & Brendan P.M. McCabe, 2018. "Approximate Bayesian forecasting," Monash Econometrics and Business Statistics Working Papers 2/18, Monash University, Department of Econometrics and Business Statistics.
    10. Worapree Maneesoonthorn & Catherine S. Forbes & Gael M. Martin, 2016. "Inference on Self-Exciting Jumps in Prices and Volatility using High Frequency Measures," Monash Econometrics and Business Statistics Working Papers 8/16, Monash University, Department of Econometrics and Business Statistics.

  4. Chris M Strickland & Gael Martin & Catherine S Forbes, 2006. "Parameterisation and Efficient MCMC Estimation of Non-Gaussian State Space Models," Monash Econometrics and Business Statistics Working Papers 22/06, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Brendan P.M. McCabe & Gael Martin & Keith Freeland, 2010. "A Quasi-locally Most powerful Test for Correlation in the conditional Variance of Positive Data," Monash Econometrics and Business Statistics Working Papers 2/10, Monash University, Department of Econometrics and Business Statistics.
    2. Hautsch, Nikolaus & Yang, Fuyu, 2012. "Bayesian inference in a Stochastic Volatility Nelson–Siegel model," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3774-3792.
    3. Stefano Grassi & Tommaso Proietti, 2010. "Characterizing economic trends by Bayesian stochastic model specification search," EERI Research Paper Series EERI_RP_2010_25, Economics and Econometrics Research Institute (EERI), Brussels.
    4. Jouchi Nakajima & Yasuhiro Omori, 2010. "Stochastic Volatility Model with Leverage and Asymmetrically Heavy-Tailed Error Using GH Skew Student's t-Distribution Models," CIRJE F-Series CIRJE-F-738, CIRJE, Faculty of Economics, University of Tokyo.
    5. Nakajima, Jouchi & Omori, Yasuhiro, 2012. "Stochastic volatility model with leverage and asymmetrically heavy-tailed error using GH skew Student’s t-distribution," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3690-3704.
    6. McCausland, William J., 2012. "The HESSIAN method: Highly efficient simulation smoothing, in a nutshell," Journal of Econometrics, Elsevier, vol. 168(2), pages 189-206.
    7. Tommaso, Proietti & Stefano, Grassi, 2010. "Bayesian stochastic model specification search for seasonal and calendar effects," MPRA Paper 27305, University Library of Munich, Germany.
    8. Kastner, Gregor & Frühwirth-Schnatter, Sylvia, 2014. "Ancillarity-sufficiency interweaving strategy (ASIS) for boosting MCMC estimation of stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 408-423.
    9. Strickland, Chris M. & Turner, Ian. W. & Denham, Robert & Mengersen, Kerrie L., 2009. "Efficient Bayesian estimation of multivariate state space models," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4116-4125, October.

  5. Chris M. Strickland & Catherine S. Forbes & Gael M. Martin, 2003. "Bayesian Analysis of the Stochastic Conditional Duration Model," Monash Econometrics and Business Statistics Working Papers 14/03, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Dinghai Xu & John Knight & Tony S. Wirjanto, 2011. "Asymmetric Stochastic Conditional Duration Model--A Mixture-of-Normal Approach," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 9(3), pages 469-488, Summer.
    2. Bauwens, L. & Galli, F., 2009. "Efficient importance sampling for ML estimation of SCD models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1974-1992, April.
    3. Brendan P.M. McCabe & Gael Martin & Keith Freeland, 2010. "A Quasi-locally Most powerful Test for Correlation in the conditional Variance of Positive Data," Monash Econometrics and Business Statistics Working Papers 2/10, Monash University, Department of Econometrics and Business Statistics.
    4. Fok, D. & Paap, R. & Franses, Ph.H.B.F., 2002. "Modeling dynamic effects of promotion on interpurchase times," Econometric Institute Research Papers EI 2002-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Joshua Chan & Rodney Strachan, 2012. "Estimation in Non-Linear Non-Gaussian State Space Models with Precision-Based Methods," CAMA Working Papers 2012-13, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    6. Chris M Strickland & Gael Martin & Catherine S Forbes, 2006. "Parameterisation and Efficient MCMC Estimation of Non-Gaussian State Space Models," Monash Econometrics and Business Statistics Working Papers 22/06, Monash University, Department of Econometrics and Business Statistics.
    7. Zhongxian Men & Tony S. Wirjanto & Adam W. Kolkiewicz, 2016. "A Multiscale Stochastic Conditional Duration Model," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 11(04), pages 1-28, December.
    8. Bayarri, M.J. & Castellanos, M.E. & Morales, J., 2006. "MCMC methods to approximate conditional predictive distributions," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 621-640, November.
    9. Strid, Ingvar, 2010. "Efficient parallelisation of Metropolis-Hastings algorithms using a prefetching approach," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2814-2835, November.
    10. Fabrizio Cipollini & Giampiero M. Gallo, 2009. "Automated Variable Selection in Vector Multiplicative Error Models," Econometrics Working Papers Archive wp2009_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    11. Ralph D. Snyder & Gael M. Martin & Phillip Gould & Paul D. Feigin, 2007. "An Assessment of Alternative State Space Models for Count Time Series," Monash Econometrics and Business Statistics Working Papers 4/07, Monash University, Department of Econometrics and Business Statistics.
    12. Trojan, Sebastian, 2014. "Modeling Intraday Stochastic Volatility and Conditional Duration Contemporaneously with Regime Shifts," Economics Working Paper Series 1425, University of St. Gallen, School of Economics and Political Science.
    13. Ng, Jason & Forbes, Catherine S. & Martin, Gael M. & McCabe, Brendan P.M., 2013. "Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models," International Journal of Forecasting, Elsevier, vol. 29(3), pages 411-430.
    14. Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54030, University Library of Munich, Germany.
    15. Patrick Leung & Catherine S. Forbes & Gael M. Martin & Brendan McCabe, 2016. "Data-driven particle Filters for particle Markov Chain Monte Carlo," Monash Econometrics and Business Statistics Working Papers 17/16, Monash University, Department of Econometrics and Business Statistics.
    16. Feigin, Paul D. & Gould, Phillip & Martin, Gael M. & Snyder, Ralph D., 2008. "Feasible parameter regions for alternative discrete state space models," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2963-2970, December.
    17. Roman Huptas, 2014. "Bayesian Estimation and Prediction for ACD Models in the Analysis of Trade Durations from the Polish Stock Market," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 6(4), pages 237-273, December.
    18. McCausland, William J., 2012. "The HESSIAN method: Highly efficient simulation smoothing, in a nutshell," Journal of Econometrics, Elsevier, vol. 168(2), pages 189-206.
    19. Galli, Fausto, 2014. "Stochastic conditonal range, a latent variable model for financial volatility," MPRA Paper 54841, University Library of Munich, Germany.
    20. Strickland, Chris M. & Turner, Ian. W. & Denham, Robert & Mengersen, Kerrie L., 2009. "Efficient Bayesian estimation of multivariate state space models," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4116-4125, October.
    21. Bortoluzzo, Adriana B. & Morettin, Pedro A. & Toloi, Clelia M. C., 2008. "Time-Varying Autoregressive Conditional Duration Model," Insper Working Papers wpe_174, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    22. Richard Gerlach & Shelton Peiris & Edward M. H. Lin, 2016. "Bayesian estimation and inference for log-ACD models," Computational Statistics, Springer, vol. 31(1), pages 25-48, March.

  6. Rachel Campbell & Catherine S. Forbes & Kees Koedijk & Paul Kofman, 2003. "Diversification Meltdown or the Impact of Fat tails on Conditional Correlation?," Monash Econometrics and Business Statistics Working Papers 18/03, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Marco Sorge, 2004. "Stress-testing financial systems: an overview of current methodologies," BIS Working Papers 165, Bank for International Settlements.
    2. Kole, Erik & Koedijk, Kees & Verbeek, Marno, 2007. "Selecting copulas for risk management," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2405-2423, August.
    3. Kole, H.J.W.G. & Koedijk, C.G. & Verbeek, M.J.C.M., 2003. "Stress Testing with Student's t Dependence," ERIM Report Series Research in Management ERS-2003-056-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    4. Albuquerque, Rui & Vega, Clara, 2006. "Asymmetric Information in the Stock Market: Economic News and Co-movement," CEPR Discussion Papers 5598, C.E.P.R. Discussion Papers.
    5. Sorge, Marco & Virolainen, Kimmo, 2006. "A comparative analysis of macro stress-testing methodologies with application to Finland," Journal of Financial Stability, Elsevier, vol. 2(2), pages 113-151, June.
    6. Kole, Erik & Koedijk, Kees & Verbeek, Marno, 2006. "Portfolio implications of systemic crises," Journal of Banking & Finance, Elsevier, vol. 30(8), pages 2347-2369, August.

  7. Gael M. Martin & Catherine S. Forbes & Vance L. Martin, 2003. "Implicit Bayesian Inference Using Option Prices," Monash Econometrics and Business Statistics Working Papers 5/03, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Gradojevic Nikola, 2016. "Multi-criteria classification for pricing European options," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(2), pages 123-139, April.
    2. Jeroen V.K. Rombouts & Lars Stentoft, 2009. "Bayesian Option Pricing Using Mixed Normal Heteroskedasticity Models," CREATES Research Papers 2009-07, Department of Economics and Business Economics, Aarhus University.
    3. G.C. Lim & G.M. Martin & V.L. Martin, 2002. "Parametric Pricing of Higher Order Moments in S&P500 Options," Monash Econometrics and Business Statistics Working Papers 1/02, Monash University, Department of Econometrics and Business Statistics.
    4. Lim, G.C. & Martin, G.M. & Martin, V.L., 2006. "Pricing currency options in the presence of time-varying volatility and non-normalities," Journal of Multinational Financial Management, Elsevier, vol. 16(3), pages 291-314, July.
    5. Renée Fry-McKibbin & Vance Martin & Chrismin Tang, 2013. "Financial Contagion and Asset Pricing," CAMA Working Papers 2013-61, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    6. Anthony D. Hall & Paul Kofman & Steve Manaster, 2001. "Migration of Price Discovery With Constrained Futures Markets," Research Paper Series 70, Quantitative Finance Research Centre, University of Technology, Sydney.
    7. C.S. Forbes & G.M. Martin & J. Wright, 2002. "Bayesian Estimation of a Stochastic Volatility Model Using Option and Spot Prices," Monash Econometrics and Business Statistics Working Papers 2/02, Monash University, Department of Econometrics and Business Statistics.
    8. Shu Wing Ho & Alan Lee & Alastair Marsden, 2011. "Use of Bayesian Estimates to determine the Volatility Parameter Input in the Black-Scholes and Binomial Option Pricing Models," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 4(1), pages 1-23, December.

  8. Catherine S. Forbes & Gael M. Martin & Jill Wright, 2003. "Bayesian Estimation of a Stochastic Volatility Model Using Option and Spot Prices: Application of a Bivariate Kalman Filter," Monash Econometrics and Business Statistics Working Papers 17/03, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Hanno Gottschalk & Elpida Nizami & Marius Schubert, 2016. "Option Pricing in Markets with Unknown Stochastic Dynamics," Papers 1602.04848, arXiv.org, revised Jan 2017.

  9. Ralph D. Snyder & Catherine S. Forbes, 2002. "Reconstructing the Kalman Filter for Stationary and Non Stationary Time Series," Monash Econometrics and Business Statistics Working Papers 14/02, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Rob Hyndman & Muhammad Akram & Blyth Archibald, 2008. "The admissible parameter space for exponential smoothing models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(2), pages 407-426, June.

  10. C.S. Forbes & G.M. Martin & J. Wright, 2002. "Bayesian Estimation of a Stochastic Volatility Model Using Option and Spot Prices," Monash Econometrics and Business Statistics Working Papers 2/02, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Nunzio Cappuccio & Diego Lubian & Davide Raggi, 2003. "MCMC Bayesian Estimation of a Skew-GED Stochastic Volatily Model," Working Papers 07/2003, University of Verona, Department of Economics.
    2. Nunzio Cappuccio & Diego Lubian & Davide Raggi, 2006. "Investigating asymmetry in US stock market indexes: evidence from a stochastic volatility model," Applied Financial Economics, Taylor & Francis Journals, vol. 16(6), pages 479-490.
    3. Silvia Centanni, 2011. "Computing option values by pricing kernel with a stochatic volatility model," Working Papers 05/2011, University of Verona, Department of Economics.

  11. Shami, R.G. & Forbes, C.S., 2000. "A structural Time Series Model with Markov Switching," Monash Econometrics and Business Statistics Working Papers 10/00, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Chin Nam Low & Heather Anderson & Ralph Snyder, 2006. "Beverridge Nelson Decomposition With Markov Switching," CAMA Working Papers 2006-18, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

  12. Forbes, C.S. & Kofman, P., 2000. "Bayesian Soft Target Zones," Monash Econometrics and Business Statistics Working Papers 4/00, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Oleg Korenok & Stanislav Radchenko, 2005. "The smooth transition autoregressive target zone model with the Gaussian stochastic volatility and TGARCH error terms with applications," Working Papers 0505, VCU School of Business, Department of Economics.
    2. Oleg Korenok & Stanislav Radchenko, 2005. "Expectations Anchoring in Inflation Targeting Regimes," Working Papers 0503, VCU School of Business, Department of Economics.
    3. Theis Lange, 2009. "First and second order non-linear cointegration models," CREATES Research Papers 2009-04, Department of Economics and Business Economics, Aarhus University.
    4. Lundbergh, Stefan & Teräsvirta, Timo, 2003. "A time series model for an exchange rate in a target zone with applications," SSE/EFI Working Paper Series in Economics and Finance 533, Stockholm School of Economics.
    5. Guangli Xu & Shiyu Song & Yongjin Wang, 2016. "The Valuation Of Options On Foreign Exchange Rate In A Target Zone," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(03), pages 1-19, May.
    6. Frédérique Bec & Anders Rahbek, 2004. "Vector equilibrium correction models with non-linear discontinuous adjustments," Econometrics Journal, Royal Economic Society, vol. 7(2), pages 628-651, December.
    7. Jesús Rodríguez López & Hugo Rodríguez Mendizábal, 2007. "The Optimal Degree of Exchange Rate Flexibility: a Target Zone Approach," Review of International Economics, Wiley Blackwell, vol. 15(4), pages 803-822, September.

  13. Catherine S. Forbes & Paul Kofman, 2000. "Bayesian Target Zones," Econometric Society World Congress 2000 Contributed Papers 0575, Econometric Society.

    Cited by:

    1. Oleg Korenok & Stanislav Radchenko, 2005. "Expectations Anchoring in Inflation Targeting Regimes," Working Papers 0503, VCU School of Business, Department of Economics.
    2. Theis Lange, 2009. "First and second order non-linear cointegration models," CREATES Research Papers 2009-04, Department of Economics and Business Economics, Aarhus University.
    3. Lundbergh, Stefan & Teräsvirta, Timo, 2003. "A time series model for an exchange rate in a target zone with applications," SSE/EFI Working Paper Series in Economics and Finance 533, Stockholm School of Economics.
    4. Jesús Rodríguez López & Hugo Rodríguez Mendizábal, 2007. "The Optimal Degree of Exchange Rate Flexibility: a Target Zone Approach," Review of International Economics, Wiley Blackwell, vol. 15(4), pages 803-822, September.

  14. Forbes, C.S. & Snyder, R.D. & Shami, R.S., 2000. "Bayesian Exponential Smoothing," Monash Econometrics and Business Statistics Working Papers 7/00, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Luis Uzeda, 2018. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Staff Working Papers 18-14, Bank of Canada.
    2. Corberán-Vallet, Ana & Bermúdez, José D. & Vercher, Enriqueta, 2011. "Forecasting correlated time series with exponential smoothing models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 252-265.
    3. J Keith Ord & Ralph D Snyder & Anne B Koehler & Rob J Hyndman & Mark Leeds, 2005. "Time Series Forecasting: The Case for the Single Source of Error State Space," Monash Econometrics and Business Statistics Working Papers 7/05, Monash University, Department of Econometrics and Business Statistics.
    4. Shami, R.G. & Forbes, C.S., 2000. "A structural Time Series Model with Markov Switching," Monash Econometrics and Business Statistics Working Papers 10/00, Monash University, Department of Econometrics and Business Statistics.
    5. Roland G. Shami & Catherine S. Forbes, 2002. "Non-linear Modelling of the Australian Business Cycle using a Leading Indicator," Monash Econometrics and Business Statistics Working Papers 5/02, Monash University, Department of Econometrics and Business Statistics.
    6. Robert R. Andrawis & Amir F. Atiya, 2009. "A new Bayesian formulation for Holt's exponential smoothing," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(3), pages 218-234.
    7. Corberán-Vallet, Ana & Bermúdez, José D. & Vercher, Enriqueta, 2011. "Forecasting correlated time series with exponential smoothing models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 252-265, April.

  15. Oliver, J.J. & Forbes, C.S., 1997. "Bayesian Approaches to Segmenting A Simple Time Series," Monash Econometrics and Business Statistics Working Papers 14/97, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Brian Hanlon & Catherine Forbes, 2002. "Model Selection Criteria for Segmented Time Series from a Bayesian Approach to Information Compression," Monash Econometrics and Business Statistics Working Papers 8/02, Monash University, Department of Econometrics and Business Statistics.

  16. Forbes, C.S. & Kalb, G.R.J. & Kofman, P., 1997. "Bayesian Arbitrage Threshold Analysis," Monash Econometrics and Business Statistics Working Papers 3/97, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Goldman Elena & Nam Jouahn & Tsurumi Hiroki & Wang Jun, 2013. "Regimes and long memory in realized volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(5), pages 521-549, December.
    2. Oscar Bajo-Rubio & Carmen Díaz-Roldán & Vicente Esteve, 2003. "Is the Budget Deficit Sustainable when Fiscal Policy is nonlinear? The Case of Spain, 1961-2001," Economic Working Papers at Centro de Estudios Andaluces E2003/32, Centro de Estudios Andaluces.
    3. Robles-Fernandez M. Dolores & Nieto Luisa & Fernandez M. Angeles, 2004. "Nonlinear Intraday Dynamics in Eurostoxx50 Index Markets," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(4), pages 1-28, December.
    4. Alexakis, Christos, 2010. "Long-run relations among equity indices under different market conditions: Implications on the implementation of statistical arbitrage strategies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(4), pages 389-403, October.
    5. Kristyna Ters & Jörg Urban, 2018. "Estimating unknown arbitrage costs: evidence from a three-regime threshold vector error correction model," BIS Working Papers 689, Bank for International Settlements.
    6. Greb, Friederike & Krivobokova, Tatyana & von Cramon-Taubadel, Stephan & Munk, Axel, 2011. "On threshold estimation in threshold vector error correction models," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114599, European Association of Agricultural Economists.
    7. Tse, Yiuman, 2001. "Index arbitrage with heterogeneous investors: A smooth transition error correction analysis," Journal of Banking & Finance, Elsevier, vol. 25(10), pages 1829-1855, October.
    8. Kim, Bong-Han & Chun, Sun-Eae & Min, Hong-Ghi, 2010. "Nonlinear dynamics in arbitrage of the S&P 500 index and futures: A threshold error-correction model," Economic Modelling, Elsevier, vol. 27(2), pages 566-573, March.
    9. Hu, Jin-Li & Lin, Cheng-Hsun, 2008. "Disaggregated energy consumption and GDP in Taiwan: A threshold co-integration analysis," Energy Economics, Elsevier, vol. 30(5), pages 2342-2358, September.
    10. Shively, Philip A., 2003. "The nonlinear dynamics of stock prices," The Quarterly Review of Economics and Finance, Elsevier, vol. 43(3), pages 505-517.
    11. Lee, Jaeram & Kang, Jangkoo & Ryu, Doojin, 2015. "Common deviation and regime-dependent dynamics in the index derivatives markets," Pacific-Basin Finance Journal, Elsevier, vol. 33(C), pages 1-22.
    12. Byeongseon Seo, 2004. "Testing for Nonlinear Adjustment in Smooth Transition Vector Error Correction Models," Econometric Society 2004 Far Eastern Meetings 749, Econometric Society.
    13. Jaeram Lee & Doojin Ryu, 2016. "Asymmetric Mispricing and Regime-dependent Dynamics in Futures and Options Markets," Asian Economic Journal, East Asian Economic Association, vol. 30(1), pages 47-65, March.

  17. Forbes, C.S. & King, M.L. & Morgan, A., 1995. "A Small Sample Variable Selection Procedure," Monash Econometrics and Business Statistics Working Papers 15/95, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Phillip Fanchon, 2003. "Variable selection for dynamic measures of efficiency in the computer industry," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 9(3), pages 175-188, August.
    2. Taylor, A. M. Robert, 1997. "On the practical problems of computing seasonal unit root tests," International Journal of Forecasting, Elsevier, vol. 13(3), pages 307-318, September.

Articles

  1. Ng, Jason & Forbes, Catherine S. & Martin, Gael M. & McCabe, Brendan P.M., 2013. "Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models," International Journal of Forecasting, Elsevier, vol. 29(3), pages 411-430.
    See citations under working paper version above.
  2. Maneesoonthorn, Worapree & Martin, Gael M. & Forbes, Catherine S. & Grose, Simone D., 2012. "Probabilistic forecasts of volatility and its risk premia," Journal of Econometrics, Elsevier, vol. 171(2), pages 217-236.
    See citations under working paper version above.
  3. Strickland, Chris M. & Martin, Gael M. & Forbes, Catherine S., 2008. "Parameterisation and efficient MCMC estimation of non-Gaussian state space models," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2911-2930, February.
    See citations under working paper version above.
  4. Campbell, Rachel A.J. & Forbes, Catherine S. & Koedijk, Kees G. & Kofman, Paul, 2008. "Increasing correlations or just fat tails?," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 287-309, March.

    Cited by:

    1. Baur, Dirk G. & Dimpfl, Thomas & Jung, Robert C., 2012. "Stock return autocorrelations revisited: A quantile regression approach," University of Tuebingen Working Papers in Economics and Finance 24, University of Tuebingen, Faculty of Economics and Social Sciences.
    2. Palmroos, Peter, 2009. "Effects of unobserved defaults on correlation between probability of default and loss given on mortgage loans," Research Discussion Papers 3/2009, Bank of Finland.
    3. Brière, Marie & Chapelle, Ariane & Szafarz, Ariane, 2012. "No contagion, only globalization and flight to quality," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1729-1744.
    4. Krämer, Walter & van Kampen, Maarten, 2011. "A simple nonparametric test for structural change in joint tail probabilities," Economics Letters, Elsevier, vol. 110(3), pages 245-247, March.
    5. Daniel Bartz & Kerr Hatrick & Christian W. Hesse & Klaus-Robert Muller & Steven Lemm, 2011. "Directional Variance Adjustment: improving covariance estimates for high-dimensional portfolio optimization," Papers 1109.3069, arXiv.org, revised Mar 2012.
    6. Kris Boudt & Jon Danielsson & Siem Jan Koopman & Andre Lucas, 2012. "Regime switches in the volatility and correlation of financial institutions," Working Paper Research 227, National Bank of Belgium.
    7. Gębka, Bartosz & Wohar, Mark E., 2013. "The determinants of quantile autocorrelations: Evidence from the UK," International Review of Financial Analysis, Elsevier, vol. 29(C), pages 51-61.
    8. Mittnik, Stefan, 2013. "VaR-implied tail-correlation matrices," CFS Working Paper Series 2013/05, Center for Financial Studies (CFS).
    9. Chester Curme & Michele Tumminello & Rosario N. Mantegna & H. Eugene Stanley & Dror Y. Kenett, 2014. "Emergence of statistically validated financial intraday lead-lag relationships," Papers 1401.0462, arXiv.org.
    10. Kaiser, Jonas & Krämer, Walter, 2011. "A cautionary note on computing conditional from unconditional correlations," Economics Letters, Elsevier, vol. 111(2), pages 176-179, May.
    11. Paulo Sergio Ceretta & Marcelo Brutti Righi & Alexandre Silva Da costa & Fernanda Maria Muller, 2012. "Quantiles autocorrelation in stock markets returns," Economics Bulletin, AccessEcon, vol. 32(3), pages 2065-2075.
    12. Dror Y. Kenett & Xuqing Huang & Irena Vodenska & Shlomo Havlin & H. Eugene Stanley, 2014. "Partial correlation analysis: Applications for financial markets," Papers 1402.1405, arXiv.org.
    13. Galeano, Pedro & Wied, Dominik, 2014. "Multiple break detection in the correlation structure of random variables," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 262-282.
    14. Becker, Christoph & Schmidt, Wolfgang M., 2015. "How past market movements affect correlation and volatility," Journal of International Money and Finance, Elsevier, vol. 50(C), pages 78-107.
    15. Josua Gösmann & Daniel Ziggel, 2018. "An innovative risk management methodology for trading equity indices based on change points," Journal of Asset Management, Palgrave Macmillan, vol. 19(2), pages 99-109, March.
    16. Ni, Zhong-Xin & Wang, Da-Zhong & Xue, Wen-Jun, 2015. "Investor sentiment and its nonlinear effect on stock returns—New evidence from the Chinese stock market based on panel quantile regression model," Economic Modelling, Elsevier, vol. 50(C), pages 266-274.
    17. Tjøstheim, Dag & Hufthammer, Karl Ove, 2013. "Local Gaussian correlation: A new measure of dependence," Journal of Econometrics, Elsevier, vol. 172(1), pages 33-48.
    18. Nicolai Bissantz & Daniel Ziggel & Kathrin Bissantz, 2011. "An Empirical Study of Correlation and Volatility Changes of Stock Indices and their Impact on Risk Figures," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 4(4), pages 127-141, August.
    19. T. Miyazaki & S. Hamori, 2016. "Asymmetric correlations in gold and other financial markets," Applied Economics, Taylor & Francis Journals, vol. 48(46), pages 4419-4425, October.
    20. Jacobs, Michael & Karagozoglu, Ahmet K., 2014. "On the characteristics of dynamic correlations between asset pairs," Research in International Business and Finance, Elsevier, vol. 32(C), pages 60-82.
    21. Tse, Chi K. & Liu, Jing & Lau, Francis C.M., 2010. "A network perspective of the stock market," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 659-667, September.
    22. Paula V. Tofoli & Flavio A. Ziegelmann & Osvaldo Candido, 2017. "A Comparison Study of Copula Models for Europea Financial Index Returns," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 9(10), pages 155-178, October.
    23. Gospodinov, Nikolay, 2017. "Asset Co-movements: Features and Challenges," FRB Atlanta Working Paper 2017-11, Federal Reserve Bank of Atlanta.
    24. Dominik Wied & Matthias Arnold & Nicolai Bissantz & Daniel Ziggel, 2012. "A new fluctuation test for constant variances with applications to finance," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(8), pages 1111-1127, November.
    25. Chang, Kuang-Liang, 2014. "The symmetrical and positive relationship between crude oil and nominal exchange rate returns," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 266-284.

  5. Catherine Forbes & Gael Martin & Jill Wright, 2007. "Inference for a Class of Stochastic Volatility Models Using Option and Spot Prices: Application of a Bivariate Kalman Filter," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 387-418.

    Cited by:

    1. Maneesoonthorn, Worapree & Martin, Gael M. & Forbes, Catherine S. & Grose, Simone D., 2012. "Probabilistic forecasts of volatility and its risk premia," Journal of Econometrics, Elsevier, vol. 171(2), pages 217-236.
    2. A. S. Hurn & K. A. Lindsay & A. J. McClelland, 2015. "Estimating the Parameters of Stochastic Volatility Models Using Option Price Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 579-594, October.
    3. Gael M. Martin & Andrew Reidy & Jill Wright, 2009. "Does the option market produce superior forecasts of noise-corrected volatility measures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(1), pages 77-104.
    4. Gael M. Martin & Brendan P.M. McCabe & Worapree Maneesoonthorn & Christian P. Robert, 2014. "Approximate Bayesian Computation in State Space Models," Monash Econometrics and Business Statistics Working Papers 20/14, Monash University, Department of Econometrics and Business Statistics.
    5. Marcel Prokopczuk & Yingying Wu, 2013. "Estimating term structure models with the Kalman filter," Chapters,in: Handbook of Research Methods and Applications in Empirical Finance, chapter 4, pages 97-113 Edward Elgar Publishing.
    6. Shu Wing Ho & Alan Lee & Alastair Marsden, 2011. "Use of Bayesian Estimates to determine the Volatility Parameter Input in the Black-Scholes and Binomial Option Pricing Models," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 4(1), pages 1-23, December.
    7. Lorenzo Mercuri & Edit Rroji, 2018. "Option pricing in an exponential MixedTS Lévy process," Annals of Operations Research, Springer, vol. 260(1), pages 353-374, January.

  6. Strickland, Chris M. & Forbes, Catherine S. & Martin, Gael M., 2006. "Bayesian analysis of the stochastic conditional duration model," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2247-2267, May.
    See citations under working paper version above.
  7. Gael M. Martin & Catherine S. Forbes & Vance L. Martin, 2005. "Implicit Bayesian Inference Using Option Prices," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(3), pages 437-462, May.
    See citations under working paper version above.
  8. Snyder Ralph D & Forbes Catherine S, 2003. "Reconstructing the Kalman Filter for Stationary and Non Stationary Time Series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(2), pages 1-20, July.
    See citations under working paper version above.
  9. Forbes, Catherine S & Kalb, Guyonne R J & Kofman, Paul, 1999. "Bayesian Arbitrage Threshold Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 364-372, July.
    See citations under working paper version above.
  10. G. M. Martin & C. S. Forbes, 1999. "Using simulation methods for bayesian econometric models: inference, development and communication: some comments," Econometric Reviews, Taylor & Francis Journals, vol. 18(1), pages 113-118.

    Cited by:

    1. Liu, Chun, 2010. "Marginal likelihood calculation for gelfand-dey and Chib Method," MPRA Paper 34928, University Library of Munich, Germany.
    2. Hibiki Ichiue & Takushi Kurozumi & Takeki Sunakawa, 2008. "Inflation Dynamics and Labor Adjustments in Japan: A Bayesian DSGE Approach," Bank of Japan Working Paper Series 08-E-9, Bank of Japan.
    3. Xibin Zhang & Maxwell L. King, 2011. "Bayesian semiparametric GARCH models," Monash Econometrics and Business Statistics Working Papers 24/11, Monash University, Department of Econometrics and Business Statistics.
    4. Dewachter, Hans & Iania, Leonardo & Lyrio, Marco, 2011. "A New-Keynesian Model of the Yield Curve with Learning Dynamics: A Bayesian Evaluation," Insper Working Papers wpe_250, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    5. Hirose, Yasuo, 2010. "Monetary policy and sunspot fluctuation in the U.S. and the Euro area," MPRA Paper 33693, University Library of Munich, Germany.
    6. Yasuo Hirose, 2008. "Equilibrium Indeterminacy and Asset Price Fluctuation in Japan: A Bayesian Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(5), pages 967-999, August.
    7. Rangan Gupta & Rudi Steinbach, 2010. "Forecasting Key Macroeconomic Variables of the South African Economy: A Small Open Economy New Keynesian DSGE-VAR Model," Working Papers 201019, University of Pretoria, Department of Economics.
    8. Warne, Anders, 2006. "Bayesian inference in cointegrated VAR models: with applications to the demand for euro area M3," Working Paper Series 692, European Central Bank.
    9. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2011. "Bayesian estimation of bandwidths for a nonparametric regression model with a flexible error density," Monash Econometrics and Business Statistics Working Papers 10/11, Monash University, Department of Econometrics and Business Statistics.
    10. Viktors Ajevskis & Kristine Vitola, 2011. "Fixed Exchange Rate Versus Inflation Targeting: Evidence from DSGE Modelling," Working Papers 2011/02, Latvijas Banka.
    11. Riggi, Marianna & Tancioni, Massimiliano, 2010. "Nominal vs real wage rigidities in New Keynesian models with hiring costs: A Bayesian evaluation," Journal of Economic Dynamics and Control, Elsevier, vol. 34(7), pages 1305-1324, July.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 18 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ETS: Econometric Time Series (10) 2002-04-25 2002-04-25 2002-04-25 2002-04-25 2002-10-23 2003-10-20 2006-12-22 2011-01-03 2013-12-29 2014-01-24. Author is listed
  2. NEP-ECM: Econometrics (9) 2002-04-25 2002-10-08 2002-10-23 2003-02-26 2003-08-17 2003-10-20 2006-12-22 2011-01-03 2013-12-29. Author is listed
  3. NEP-FMK: Financial Markets (4) 2002-04-25 2002-04-25 2003-02-24 2003-10-20
  4. NEP-MST: Market Microstructure (3) 2006-12-22 2013-12-29 2014-01-24
  5. NEP-RMG: Risk Management (3) 2003-02-24 2003-10-20 2011-01-03
  6. NEP-CMP: Computational Economics (2) 2002-04-25 2003-08-17
  7. NEP-FIN: Finance (2) 2002-10-08 2003-02-24
  8. NEP-CFN: Corporate Finance (1) 2003-10-20
  9. NEP-FOR: Forecasting (1) 2011-01-03
  10. NEP-IAS: Insurance Economics (1) 2006-09-03
  11. NEP-IFN: International Finance (1) 2002-04-25
  12. NEP-ORE: Operations Research (1) 2011-01-03

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Catherine Scipione Forbes should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.